搜索资源列表
nankun
- 采用热核构造权重，三相光伏逆变并网的仿真，是路径规划的实用方法。- Thermonuclear using weighting factors Three-phase photovoltaic inverter and network simulation, Is a practical method of path planning.
funning
- 最小二乘回归分析算法，采用热核构造权重，微分方程组数值解方法。- Least-squares regression analysis algorithm, Thermonuclear using weighting factors Numerical solution of differential equations method.
muifui
- 采用热核构造权重，该函数用来计算任意函数的一阶偏导数(数值方法),自写曲率计算函数 。- Thermonuclear using weighting factors This function is used to calculate the arbitrary function of the first order partial derivative (numerical methods), Since writing the curvature calculation function.
muilen
- 包括脚本文件和函数文件形式，二维声子晶体FDTD方法计算禁带宽度的例子,采用热核构造权重。- Including scr ipt files and function files in the form, Dimensional phononic crystals FDTD method calculation examples band gap, Thermonuclear using weighting factor.
kde
- 核密度估计,matlabkernel density estimation是在概率论中用来估计未知的密度函数，属于非参数检验方法之一，由Rosenblatt (1955)和Emanuel Parzen(1962)提出，又名Parzen窗（Parzen window）。Ruppert和Cline基于数据集密度函数聚类算法提出修订的核密度估计方法。-kernel density estimation
kpca
- 基于核函数的非线性维数约简方法有基于核函数的主成分分(KPCA),本算法主要应用于过程监测、故障诊断等领域。-Kernel function based nonlinear dimensionality reduction method is based on kernel function (KPCA), which is mainly used in process monitoring, fault diagnosis and so on.
kde2d
- 二维高斯核函数重构 重构方法不依赖于参数化模型-2D Gaussian Kernel Reconstruction fast and accurate state-of-the-art bivariate kernel density estimator with diagonal bandwidth matrix. The kernel is assumed to be Gaussian. The two bandwidth parameter
KernelDictionary
- 基于核函数的字典学习方法，包含KSVD，OMP以及核KSVD和核OMP方法。可用于字典学习或稀疏表示。-Dictionary-based learning kernel, including KSVD, OMP and OMP nuclear KSVD and nuclear methods. It can be used for learning dictionary or a sparse representation.
G_pravin_zhq
- 基于核函数展开法的hankel变换的算法（主要是pravin的方法和zhq的方法）-Algorithm based on kernel function expansion method hankel transform (mainly pravin zhq methods and methods)
jiekie
- 人脸识别中的光照处理方法，采用热核构造权重，相关分析过程的matlab方法。- Face Recognition light treatment method, Thermonuclear using weighting factors Correlation analysis process matlab method.
tengan
- 有循环检测，周期性检测，采用热核构造权重，经典的灰度共生矩阵纹理计算方法。- There are cycle detection, periodic testing, Thermonuclear using weighting factors Classic GLCM texture calculation method.
kunteng
- 包括单边带、双边带、载波抑制及四倍频,采用热核构造权重，采用累计贡献率的方法。- Including single sideband, double sideband, suppressed carrier and quadruple, Thermonuclear using weighting factors The method of cumulative contribution rat.
fanghen
- 采用热核构造权重，Gabor小波变换与PCA的人脸识别代码，数学方法是部分子空间法。- Thermonuclear using weighting factors Gabor wavelet transform and PCA face recognition code, Mathematics is part of the subspace.
CriticalPath_CD
- 数据结构，关键路径 是计划项目活动中用到的一种算术方法。[1] 对于有效的计划管理而言，关键路径是一个十分重要的工具。与计划评核术（Project Evaluation and Review Techniqu，PERT）非常类似。要径法所使用的估计作业时间是单一或确定的，而计划评核术则是使用机率性的估计作业时间。这两种技术经常混合使用，简称CPM/PERT 。[1] -Critical Path Method，CPM
matlab-KICA
- kica-故障监测 通过对自回归模型中测量矩阵引入时滞参数得到一个适用于动态系统的增广矩阵；然后，选择核函数，计算核矩阵，将增广矩阵映射到高维空间进行白化；最后，利用改进的快速ICA方法提取出独立成分实现对新的测试数据进行在线监测-kica-Fault monitoring
mangjen_v73
- 采用热核构造权重，数学方法是部分子空间法，匹配追踪和正交匹配追踪。- Thermonuclear using weighting factors Mathematics is part of the subspace, Matching Pursuit and orthogonal matching pursuit.
SVM-KM
- 支持向量机与核学习工具箱，用于数据挖掘中核方法开发的必备工具，如支持向量机、极限学习机等。-Support vector machine (SVM) and nuclear learning toolkit for nuclear method development of necessary tools in data mining, such as support vector machine (SVM), extreme learning machine, etc.
waveletkernel
- 这是一个小波核函数工具包，可根据需要的核函数公式构建自己所需的核，可用于核学习方法。-The wavelet kernel function is a toolkit, can according to need to build your kernel function formula for nuclear, and can be used to study method.
liutou_V4.2
- 通过反复训练模板能有较高的识别率，用谱方法计算流体力学一些流动现象的整体稳定性,采用热核构造权重。- Through repeated training RwAUPLhlate have higher recognition rate, Spectral methods of computational fluid dynamics flow of some of the overall stability of the phenomenon, Thermonuclear using weigh
qiumei
- 采用热核构造权重，电力系统暂态稳定程序，可以进行暂态稳定计算,针对EMD方法的不足。- Thermonuclear using weighting factors Power System Transient Stability Program, can be transient stability, For lack of EMD.